diff --git a/bob/learn/misc/cpp/IVectorTrainer.cpp b/bob/learn/misc/cpp/IVectorTrainer.cpp
index be843b20e3347a79a24ceac835ce8ad0b2eeec84..4f929af95a62fa232f73f6d529e9ca8e8d849c43 100644
--- a/bob/learn/misc/cpp/IVectorTrainer.cpp
+++ b/bob/learn/misc/cpp/IVectorTrainer.cpp
@@ -15,7 +15,6 @@
#include <bob.math/linear.h>
#include <bob.math/linsolve.h>
#include <boost/shared_ptr.hpp>
-#include <boost/random.hpp>
bob::learn::misc::IVectorTrainer::IVectorTrainer(const bool update_sigma,
const double convergence_threshold,
diff --git a/bob/learn/misc/cpp/KMeansTrainer.cpp b/bob/learn/misc/cpp/KMeansTrainer.cpp
index ae69ee740a482b9eb6c6c739970496f5ccd74f9f..092c87d48698d46e4a45d1ac03a0c4337b5ed04a 100644
--- a/bob/learn/misc/cpp/KMeansTrainer.cpp
+++ b/bob/learn/misc/cpp/KMeansTrainer.cpp
@@ -8,11 +8,9 @@
#include <bob.learn.misc/KMeansTrainer.h>
#include <bob.core/array_copy.h>
-#include <boost/random.hpp>
+#include <bob.core/random.h>
-#if BOOST_VERSION >= 104700
-#include <boost/random/discrete_distribution.hpp>
-#endif
+#include <boost/random.hpp>
bob::learn::misc::KMeansTrainer::KMeansTrainer(double convergence_threshold,
size_t max_iterations, bool compute_likelihood, InitializationMethod i_m):
@@ -71,9 +69,7 @@ void bob::learn::misc::KMeansTrainer::initialize(bob::learn::misc::KMeansMachine
// assign the i'th mean to a random example within the i'th chunk
blitz::Range a = blitz::Range::all();
-#if BOOST_VERSION >= 104700
if(m_initialization_method == RANDOM || m_initialization_method == RANDOM_NO_DUPLICATE) // Random initialization
-#endif
{
unsigned int n_chunk = n_data / kmeans.getNMeans();
size_t n_max_trials = (size_t)n_chunk * 5;
@@ -83,11 +79,10 @@ void bob::learn::misc::KMeansTrainer::initialize(bob::learn::misc::KMeansMachine
for(size_t i=0; i<kmeans.getNMeans(); ++i)
{
- boost::uniform_int<> range(i*n_chunk, (i+1)*n_chunk-1);
- boost::variate_generator<boost::mt19937&, boost::uniform_int<> > die(*m_rng, range);
+ boost::uniform_int<> die(i*n_chunk, (i+1)*n_chunk-1);
// get random index within chunk
- unsigned int index = die();
+ unsigned int index = die(*m_rng);
// get the example at that index
blitz::Array<double, 1> mean = ar(index,a);
@@ -110,7 +105,7 @@ void bob::learn::misc::KMeansTrainer::initialize(bob::learn::misc::KMeansMachine
break;
else
{
- index = die();
+ index = die(*m_rng);
mean = ar(index,a);
++count;
}
@@ -127,14 +122,12 @@ void bob::learn::misc::KMeansTrainer::initialize(bob::learn::misc::KMeansMachine
kmeans.setMean(i, mean);
}
}
-#if BOOST_VERSION >= 104700
else // K-Means++
{
// 1.a. Selects one sample randomly
- boost::uniform_int<> range(0, n_data-1);
- boost::variate_generator<boost::mt19937&, boost::uniform_int<> > die(*m_rng, range);
+ boost::uniform_int<> die(0, n_data-1);
// Gets the example at a random index
- blitz::Array<double,1> mean = ar(die(),a);
+ blitz::Array<double,1> mean = ar(die(*m_rng),a);
kmeans.setMean(0, mean);
// 1.b. Loops, computes probability distribution and select samples accordingly
@@ -160,12 +153,11 @@ void bob::learn::misc::KMeansTrainer::initialize(bob::learn::misc::KMeansMachine
// Takes a sample according to the weights distribution
// Blitz iterators is fine as the weights array should be C-style contiguous
bob::core::array::assertCContiguous(weights);
- boost::random::discrete_distribution<> die2(weights.begin(), weights.end());
+ bob::core::random::discrete_distribution<> die2(weights.begin(), weights.end());
blitz::Array<double,1> new_mean = ar(die2(*m_rng),a);
kmeans.setMean(m, new_mean);
}
}
-#endif
// Resize the accumulator
m_zeroethOrderStats.resize(kmeans.getNMeans());
m_firstOrderStats.resize(kmeans.getNMeans(), kmeans.getNInputs());
diff --git a/bob/learn/misc/cpp/PLDATrainer.cpp b/bob/learn/misc/cpp/PLDATrainer.cpp
index 2c687f30e2a2fc8a02a1581895c386f0818cb96f..725dd45b509d88926f48bd2afce5c13a1ce8f72d 100644
--- a/bob/learn/misc/cpp/PLDATrainer.cpp
+++ b/bob/learn/misc/cpp/PLDATrainer.cpp
@@ -14,7 +14,6 @@
#include <bob.math/inv.h>
#include <bob.math/svd.h>
#include <algorithm>
-#include <boost/random.hpp>
#include <vector>
#include <limits>
diff --git a/bob/learn/misc/include/bob.learn.misc/IVectorTrainer.h b/bob/learn/misc/include/bob.learn.misc/IVectorTrainer.h
index 91f28ac90fb87ceb62bde3e11651285a70e92ee4..f3e82254d01e24c67d472280fabd2130752bff3e 100644
--- a/bob/learn/misc/include/bob.learn.misc/IVectorTrainer.h
+++ b/bob/learn/misc/include/bob.learn.misc/IVectorTrainer.h
@@ -13,7 +13,6 @@
#include <bob.learn.misc/IVectorMachine.h>
#include <bob.learn.misc/GMMStats.h>
#include <boost/shared_ptr.hpp>
-#include <boost/random.hpp>
#include <vector>
namespace bob { namespace learn { namespace misc {
diff --git a/bob/learn/misc/old/ivector_trainer.cc b/bob/learn/misc/old/ivector_trainer.cc
index 8b964a832799ef492d6201b66d0bbfde4d7e4269..72328bd8f55cb9aeea1f5924f88c98623bbc33fb 100644
--- a/bob/learn/misc/old/ivector_trainer.cc
+++ b/bob/learn/misc/old/ivector_trainer.cc
@@ -83,7 +83,7 @@ static void py_set_AccSnormij(bob::learn::misc::IVectorTrainer& trainer,
// include the random API of bob.core
-#include <bob.core/random.h>
+#include <bob.core/random_api.h>
static boost::python::object ITB_getRng(EMTrainerIVectorBase& self){
// create new object
PyObject* o = PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type,0);
diff --git a/bob/learn/misc/old/jfa_trainer.cc b/bob/learn/misc/old/jfa_trainer.cc
index a5966e27b5c32718863253aed8e5695c55ce88d7..542c33ab8f987658997ab7c927bf07d4c8a56d31 100644
--- a/bob/learn/misc/old/jfa_trainer.cc
+++ b/bob/learn/misc/old/jfa_trainer.cc
@@ -311,7 +311,7 @@ static void jfa_set_accDA2(bob::learn::misc::JFATrainer& trainer,
// include the random API of bob.core
-#include <bob.core/random.h>
+#include <bob.core/random_api.h>
static boost::python::object isv_getRng(bob::learn::misc::ISVTrainer& self){
// create new object
PyObject* o = PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type,0);
diff --git a/bob/learn/misc/old/kmeans_trainer.cc b/bob/learn/misc/old/kmeans_trainer.cc
index 4ef008bb01702da3555c8aa0f22b48fb6ae0fcc2..0b90db77d5bcfbea5d927da0220bae8d87762c03 100644
--- a/bob/learn/misc/old/kmeans_trainer.cc
+++ b/bob/learn/misc/old/kmeans_trainer.cc
@@ -57,7 +57,7 @@ static void py_mStep(EMTrainerKMeansBase& trainer,
}
// include the random API of bob.core
-#include <bob.core/random.h>
+#include <bob.core/random_api.h>
static boost::python::object KMTB_getRng(EMTrainerKMeansBase& self){
// create new object
PyObject* o = PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type,0);
diff --git a/bob/learn/misc/old/main.cc b/bob/learn/misc/old/main.cc
index c8a483428957898d347542c6bd082d95789b3ce2..16f7f9ba565063a449f54451489bb4ba88282e53 100644
--- a/bob/learn/misc/old/main.cc
+++ b/bob/learn/misc/old/main.cc
@@ -14,7 +14,7 @@
#include <bob.blitz/capi.h>
#include <bob.blitz/cleanup.h>
#include <bob.io.base/api.h>
-#include <bob.core/random.h>
+#include <bob.core/random_api.h>
#include "ndarray.h"
diff --git a/bob/learn/misc/old/plda_trainer.cc b/bob/learn/misc/old/plda_trainer.cc
index a9a9de3e24def7637fbf93e25c86253989955d01..c68444496c8940d640d7844e1967c9c0dca72f5f 100644
--- a/bob/learn/misc/old/plda_trainer.cc
+++ b/bob/learn/misc/old/plda_trainer.cc
@@ -93,7 +93,7 @@ static object get_z_second_order(bob::learn::misc::PLDATrainer& m) {
// include the random API of bob.core
-#include <bob.core/random.h>
+#include <bob.core/random_api.h>
static boost::python::object TB_getRng(EMTrainerPLDA& self){
// create new object
PyObject* o = PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type,0);